Abhinav Venigalla

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 23 citations into it
• Optimization & Training — 23 citations into it
• Computer Vision and Pattern Recognition — 20 citations into it
• Model Architectures — 5 citations into it

Whom Abhinav Venigalla trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Kaiming He
2. Alex Krizhevsky
3. X. Zhang
4. Gabriel Goh
5. Geoffrey E. Hinton
6. Shaoqing Ren
7. Jia Deng
8. Karen Simonyan
9. Yoshua Bengio
10. Ross B. Girshick

Papers from Abhinav Venigalla's perspective

Ordered by how strongly the researchers Abhinav Venigalla trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. ImageNet: A large-scale hierarchical image database
4. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
5. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Gradient-based learning applied to document recognition
8. Attention is All you Need (Neural Information Processing Systems)
9. Long Short-Term Memory
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Pipelined Backpropagation at Scale: Training Large Models without Batches (2020) — 39 citations